Supplementary data for the paper 'External human-machine interfaces: Effects of message perspective'

Future automated vehicles may be equipped with external Human-Machine Interfaces (eHMIs). Currently, little is known about the effect of the perspective of the eHMI message on crossing decisions of pedestrians. We performed an experiment to examine the effects of images depicting eHMI messages of different perspectives (egocentric from the pedestrian’s point of view: WALK, DON’T WALK, allocentric: BRAKING, DRIVING, and ambiguous: GO, STOP) on participants’ (<em>N</em> = 103) crossing decisions, response times, and eye movements. Considering that crossing the road can be cognitively demanding, we added a memory task in two-thirds of the trials. The results showed that egocentric messages yielded higher subjective clarity ratings than the other messages as well as higher objective clarity scores (i.e., more uniform crossing decisions) and faster response times than the allocentric BRAKING and the ambiguous STOP. When participants were subjected to the memory task, pupil diameter increased, and crossing decisions were reached faster as compared to trials without memory task. Regarding the ambiguous messages, most participants crossed for the GO message and did not cross for the STOP message, which points towards an egocentric perspective taken by the participant. More lengthy text messages (e.g., DON’T WALK) yielded a higher number of saccades but did not cause slower response times. We conclude that pedestrians find egocentric eHMI messages clearer than allocentric ones, and take an egocentric perspective if the message is ambiguous. Our results may have important implications, as the consensus among eHMI researchers appears to be that egocentric text-based eHMIs should not be used in traffic.

未来的自动驾驶车辆可能会配备外部人机交互界面（external Human-Machine Interfaces，eHMIs）。目前学界对eHMI信息的呈现视角对行人过街决策的影响尚缺乏充分认知。本研究开展了一项实验，探究不同视角的eHMI信息图像对（N=103）名被试过街决策、反应时与眼动指标的影响：其中以行人自身视角出发的以自我为中心（egocentric）视角信息包括「WALK（通行）」「DON’T WALK（禁止通行）」，以车辆视角出发的以客体为中心（allocentric）视角信息包括「BRAKING（制动）」「DRIVING（行驶）」，模糊视角信息包括「GO（通行）」「STOP（停止）」。考虑到过街行为存在较高的认知负荷，本研究在三分之二的试次中增设了记忆任务。结果表明，相较于其他类型信息，以自我为中心的eHMI信息的主观清晰度评分更高，且客观清晰度得分（即过街决策更趋一致）、反应速度均优于以客体为中心的「BRAKING（制动）」与模糊视角的「STOP（停止）」信息。当被试需要完成记忆任务时，其瞳孔直径较无记忆任务的试次有所增大，且过街决策速度更快。针对模糊视角的信息，绝大多数被试对「GO（通行）」选择过街，对「STOP（停止）」选择不过街，这表明被试在理解信息时采用了以自我为中心的视角。更长的文本信息（如「DON’T WALK（禁止通行）」）会引发更多的眼跳次数，但并未延长反应时。本研究得出结论：行人认为以自我为中心的eHMI信息比以客体为中心的信息更清晰，且当信息模糊时会默认采用以自我为中心的视角进行解读。值得注意的是，当前eHMI领域研究者普遍认为不应在交通场景中使用基于文本的以自我为中心eHMI，本研究结果或将对该共识产生重要影响。